The OUTPUT statement saves statistics and BY variables in an output data set. When you use a BY statement, each observation in the OUT= data set corresponds to one of the BY groups. Otherwise, the OUT= data set contains only one observation.

You can use any number of OUTPUT statements in the UNIVARIATE procedure. Each OUTPUT statement creates a new data set containing the statistics specified in that statement. You must use the VAR statement with the OUTPUT statement. The OUTPUT statement must contain a specification of the form keyword=names or the PCTLPTS= and PCTLPRE= specifications. See Example 4.7 and Example 4.8.

OUT=SAS-data-set

identifies the output data set. If SAS-data-set does not exist, PROC UNIVARIATE creates it. If you omit OUT=, the data set is named DATAn, where n is the smallest integer that makes the name unique.

keyword=names

specifies the statistics to include in the output data set and gives names to the new variables that contain the statistics. Specify a keyword for each desired statistic, followed by an equal sign, followed by the names of the variables to contain the statistic. In the output data set, the first variable listed after a keyword in the OUTPUT statement contains the statistic for the first variable listed in the VAR statement, the second variable contains the statistic for the second variable in the VAR statement, and so on. If the list of names following the equal sign is shorter than the list of variables in the VAR statement, the procedure uses the names in the order in which the variables are listed in the VAR statement. The available keywords are listed in the following tables:

Table 4.43 Descriptive Statistic Keywords

Keyword

Description

CSS

corrected sum of squares

CV

coefficient of variation

KURTOSIS

kurtosis

MAX

largest value

MEAN

sample mean

MIN

smallest value

MODE

most frequent value

N

sample size

NMISS

number of missing values

NOBS

number of observations

RANGE

range

SKEWNESS

skewness

STD

standard deviation

STDMEAN

standard error of the mean

SUM

sum of the observations

SUMWGT

sum of the weights

USS

uncorrected sum of squares

VAR

variance

Table 4.44 Quantile Statistic Keywords

Keyword

Description

P1

1st percentile

P5

5th percentile

P10

10th percentile

Q1

lower quartile (25th percentile)

MEDIAN

median (50th percentile)

Q3

upper quartile (75th percentile)

P90

90th percentile

P95

95th percentile

P99

99th percentile

QRANGE

interquartile range (Q3 - Q1)

Table 4.45 Robust Statistics Keywords

Keyword

Description

GINI

Gini’s mean difference

MAD

median absolute difference about the median

QN

, alternative to MAD

SN

, alternative to MAD

STD_GINI

Gini’s standard deviation

STD_MAD

MAD standard deviation

STD_QN

standard deviation

STD_QRANGE

interquartile range standard deviation

STD_SN

standard deviation

Table 4.46 Hypothesis Testing Keywords

Keyword

Description

MSIGN

sign statistic

NORMALTEST

test statistic for normality

SIGNRANK

signed rank statistic

PROBM

probability of a greater absolute value for the sign statistic

PROBN

probability value for the test of normality

PROBS

probability value for the signed rank test

PROBT

probability value for the Student’s test

T

statistic for the Student’s test

The UNIVARIATE procedure automatically computes the 1st, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 99th percentiles for the data. These can be saved in an output data set by using keyword=names specifications. For additional percentiles, you can use the following percentile-options.

PCTLPTS=percentiles

specifies one or more percentiles that are not automatically computed by the UNIVARIATE procedure. The PCTLPRE= and PCTLPTS= options must be used together. You can specify percentiles with an expression of the form start TO stop BY increment where start is a starting number, stop is an ending number, and increment is a number to increment by. The PCTLPTS= option generates additional percentiles and outputs them to a data set. These additional percentiles are not printed.

To compute the 50th, 95th, 97.5th, and 100th percentiles, submit the statement

output pctlpre=P_ pctlpts=50,95 to 100 by 2.5;

PROC UNIVARIATE computes the requested percentiles based on the method that you specify with the PCTLDEF= option in the PROC UNIVARIATE statement. You must use PCTLPRE=, and optionally PCTLNAME=, to specify variable names for the percentiles. For example, the following statements create an output data set named Pctls that contains the 20th and 40th percentiles of the analysis variables PreTest and PostTest:

PROC UNIVARIATE saves the 20th and 40th percentiles for PreTest and PostTest in the variables PreTest_P20, PostTest_P20, PreTest_P40, and PostTest_P40.

PCTLPRE=prefixes

specifies one or more prefixes to create the variable names for the variables that contain the PCTLPTS= percentiles. To save the same percentiles for more than one analysis variable, specify a list of prefixes. The order of the prefixes corresponds to the order of the analysis variables in the VAR statement. The PCTLPRE= and PCTLPTS= options must be used together.

The procedure generates new variable names by using the prefix and the percentile values. If the specified percentile is an integer, the variable name is simply the prefix followed by the value. If the specified value is not an integer, an underscore replaces the decimal point in the variable name, and decimal values are truncated to one decimal place. For example, the following statements create the variables pwid20, pwid33_3, pwid66_6, and pwid80 for the 20th, 33.33rd, 66.67th, and 80th percentiles of Width, respectively:

If you request percentiles for more than one variable, you should list prefixes in the same order in which the variables appear in the VAR statement. If combining the prefix and percentile value results in a name longer than 32 characters, the prefix is truncated so that the variable name is 32 characters.

PCTLNAME=suffixes

specifies one or more suffixes to create the names for the variables that contain the PCTLPTS= percentiles. PROC UNIVARIATE creates a variable name by combining the PCTLPRE= value and suffix name. Because the suffix names are associated with the percentiles that are requested, list the suffix names in the same order as the PCTLPTS= percentiles. If you specify suffixes with the PCTLNAME= option and percentile values with the PCTLPTS= option where , the suffixes are used to name the first percentiles and the default names are used for the remaining percentiles. For example, consider the following statements:

The value twenty in the PCTLNAME= option is used for only the first percentile in the PCTLPTS= list. This suffix is appended to the values in the PCTLPRE= option to generate the new variable names pltwenty, pwtwenty, and phtwenty, which contain the 20th percentiles for Length, Width, and Height, respectively. Because a second PCTLNAME= suffix is not specified, variable names for the 40th percentiles for Length, Width, and Height are generated using the prefixes and percentile values. Thus, the output data set contains the variables pltwenty, pl40, pwtwenty, pw40, phtwenty, and ph40.

You must specify PCTLPRE= to supply prefix names for the variables that contain the PCTLPTS= percentiles.

If the number of PCTLNAME= values is fewer than the number of percentiles or if you omit PCTLNAME=, PROC UNIVARIATE uses the percentile as the suffix to create the name of the variable that contains the percentile. For an integer percentile, PROC UNIVARIATE uses the percentile. Otherwise, PROC UNIVARIATE truncates decimal values of percentiles to two decimal places and replaces the decimal point with an underscore.

If either the prefix and suffix name combination or the prefix and percentile name combination is longer than 32 characters, PROC UNIVARIATE truncates the prefix name so that the variable name is 32 characters.